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import streamlit as st
from sklearn import neighbors, datasets
with st.form(key='my_form'):
sLen = st.slider('Sepal lenght(cm) ', 0.0, 10.0)
sWid = st.slider('Sepal width(cm) ', 0.0, 10.0)
pLen = st.slider('Petal lenght(cm) ', 0.0, 10.0)
pWid = st.slider('Petal width(cm) ', 0.0, 10.0)
st.form_submit_button('Predict')
iris = datasets.load_iris()
X,y = iris.data, iris.target
knn = neighbors.KNeighborsClassifier(n_neighbors=3) #k = 3,4,5,6
knn.fit(X,y)
predict = knn.predict([[sLen,sWid,pLen,pWid]])
st.text(iris.target_names[predict]) |